Cases13 cases

6 to 10 of 13

1. IL-0315 Railway's backend API went down when an index build locked a billion-row Postgres table and used up every connection

   Railway2025

   Symptoms

   At 18:36 UTC on 28 October 2025, two minutes after a database change went live in production, Railway's internal monitoring alerted and paged the engineering team. The dashboard could not be opened, CLI operations that use the API, such as railway up, failed, GitHub-based deployments were delayed because webhook processing failed, and all Railway Public API operations were disrupted.

   Service outageLock contention or deadlockDatabase overload

   Trigger

   A routine schema change to the backend's Postgres database, introduced at 18:23 UTC and live in production at 18:34 UTC, that added a new column with an index without the CONCURRENTLY option.

   Root cause

   Faulty deployment

   Component

   DatabaseDatabase proxy and connection pooler

   Contributing factor

   No configuration testsLimited debug access

   Detection

   Internal monitoring alerts paged the engineering team at 18:36 UTC, and the incident was declared at 18:41 UTC.

   Remediation

   • The index migration finished after about 30 minutes and released the table lock, and the queued operations and connection pools recovered

   Action items

   • Enforce CONCURRENTLY for all index creation in CI and block pull requests that do not use it
   • Adjust PgBouncer pool limits so they cannot overwhelm the Postgres instance's capacity
   • Configure database user connection limits so administrative access stays possible during incidents

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2. IL-0368 PlanetScale's control plane went down and some database branches failed queries during the AWS us-east-1 outage

   PlanetScale2025

   Symptoms

   At 7:13 UTC on 20 October 2025, PlanetScale's continuous tests in production started failing because they could not create new database branches. The service that creates, resizes and configures database branches was unavailable, a near-total control plane outage, while existing database branches kept their capacity and connectivity.

   Service outageScale-up failureNetwork unreachableHigh error rateReplication lagDNS resolution failures

   Trigger

   The incident started with a DNS misconfiguration at one of PlanetScale's service providers. An Amazon DynamoDB outage impacted AWS STS, and several hours of capacity constraints and network instability in AWS us-east-1 followed.

   Root cause

   Cloud provider outage

   Component

   DatabaseDatabase replicationDatabase proxy and connection poolerObject storage

   Contributing factor

   –

   Detection

   PlanetScale's continuous testing in production started failing and alerted engineers at 7:13 UTC. At 10:05 UTC an alert fired for a Kubernetes operator in a large single-tenant customer installation exhausting its resources.

   Remediation

   • Disallowed new databases in us-east-1 and made us-east-2 the default region for new databases
   • Delayed new backups and cancelled pending backups that were waiting for an EC2 instance
   • Advised PlanetScale Managed customers with vtgate autoscaling to shed load
   • Paused draining and terminating EC2 instances older than 30 days
   • Kept vacant EC2 instances for reuse instead of terminating them
   • Bin-packed vtgate processes more tightly for customers with autoscaling
   • Sent manual reparent requests to move primaries to healthier availability zones
   • Restarted the edge load balancer and vtgate processes that did not recover after the partitions healed

   Action items

   • Understand and become resilient to the failure modes of SaaS dependencies for CI/CD, SSO, web application hosting and incident communication
   • Investigate more ambitious ways to reduce runtime dependence on internal and AWS services
   • Look into using all six us-east-1 availability zones to tolerate zonal outages and partitions

   Lessons

   Keeping the control plane separate from the data plane meant the control plane outage did not affect customer databases, and redundancy, automated failover and zonal traffic routing limited the effect of the network partitions. Network partitions are hard to reason about, test and tolerate: with three availability zones a system survives losing one zone only if the other two can still reach each other reliably.

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3. IL-0316 Railway's control plane slowed and deployments stopped after a PgBouncer version jump used abnormal CPU and memory

   Railway2025

   Symptoms

   At 11:48 UTC on 22 September 2025, minutes after Railway had resolved a dashboard outage, its control plane showed abnormal resource consumption and elevated API latency. A large backlog of deployments queued during the first outage had started all at once, and the control plane began returning elevated database errors.

   High latencyIntermittent timeoutsDeploys failing

   Trigger

   After a dashboard outage caused by a schema change was fixed, a large backlog of queued deployments started at the same time and put the control plane and its database, behind a newly upgraded PgBouncer, under heavy load.

   Root cause

   Breaking change in an upgrade

   Component

   DatabaseDatabase proxy and connection pooler

   Contributing factor

   Unpinned versionNo staged rolloutMonitoring blind spotUnreviewed defaults

   Detection

   Users reported at 11:05 UTC that the project canvas failed to load; the control plane's abnormal resource consumption and elevated API latency were seen at 11:48 UTC and opened as a new incident.

   Remediation

   • Deployed a fix for the API failure caused by the schema change within 15 minutes
   • Suspended deployments for non-Pro users so Pro users could deploy and the queue could drain
   • Suspended all deployments, Pro included, for up to 20 minutes during peak instability
   • Scaled up the control plane database's CPU, memory, connection limits and IOPS
   • Rolled PgBouncer back to the previous stable version, which brought all metrics back to nominal
   • Re-enabled deployments for all non-Pro users
   • Fixed the edge case in which private networks and their endpoints were missing from the dashboard

   Action items

   • Re-engineer parts of the control plane to be more resilient, moving large parts of its storage layer away from Postgres
   • Add CI validation that keeps disruptive schema changes out of production and automated schema compatibility checks before backend deployments
   • Monitor and alert on PgBouncer node CPU, memory and connection pool utilization
   • Upgrade PgBouncer in phases, instance by instance, instead of everywhere at once

   Lessons

   Railway believes that without the breaking schema change reaching production the cascade would not have happened, that monitoring PgBouncer's own CPU, memory and pool metrics would have shown the performance regression earlier and shortened recovery, and that upgrading PgBouncer instances one at a time would have exposed the version-specific problem before it reached every instance.

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4. IL-0498 Clerk's Postgres database had load spikes every 15 minutes and requests failed and slowed intermittently for four days

   Clerk2025

   Symptoms

   At 13:08 UTC on 15 September 2025, Clerk's internal monitoring alerted on significant request failures and increased latency. Over the following days the request failures and latency spikes kept coming back while the Postgres database stayed unhealthy, with repeated spikes in database load.

   High error rateHigh latencyDatabase overloadConnection pool exhaustion

   Trigger

   At 05:30 UTC on 14 September 2025 the cloud provider automatically upgraded Clerk's Postgres database to a new minor version, which changed how Postgres handled connection locks.

   Root cause

   Breaking change in an upgrade

   Component

   DatabaseDatabase proxy and connection pooler

   Contributing factor

   Unpinned versionRetry stormMonitoring blind spotOverlapping failuresHarmful manual action

   Detection

   Internal monitoring alerted on significant request failures and increased latency at 13:08 UTC on 15 September. Shortly after the upgrade on 14 September it had already shown an increased but still acceptable database load.

   Remediation

   • Optimised several expensive queries, refined critical indexes and re-indexed the database
   • Blocked abusive traffic more aggressively for a time
   • Performed a manual minor version upgrade and increased database capacity
   • Added jitter to the connection pooling configuration so connections no longer recycled in step

   Action items

   • Evaluate other database providers that give more control over upgrades and downgrades
   • Isolate more services from each other, for example Sign Up and Sign In infrastructure from the rest of the system
   • Keep optimising the most costly database queries
   • Evaluate sharding and multi-tenant infrastructure to isolate one application from others

   Lessons

   Clerk's review found that connection metrics sampled every 60 seconds could not show a recycling pattern that lasted seconds and repeated every 15 minutes, that an attack and background jobs with similar periods pulled attention away from the database layer, that the Backend API looked healthy only because it manages far fewer connections, and that the release freeze removed the staggering of connection creation that normal deploys provide.

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5. IL-0307 Supabase's Postgres connection pooler Supavisor 2.0 dropped connections for about 80% of us-east-1 tenants

   Supabase2025

   Symptoms

   At 16:05 UTC on January 29, 2025, most clients connected through Supavisor, Supabase's Postgres connection pooler, in us-east-1 were disconnected and could not reconnect reliably. Connections dropped for about 80% of tenants, and Supabase Storage connectivity also failed until the pooler was fixed.

   Connection resetsIntermittent connection failures

   Trigger

   The planned upgrade of Supavisor to version 2.0 in us-east-1, which completed at 14:46 UTC.

   Root cause

   Faulty deployment

   Component

   Database proxy and connection poolerDatabase

   Contributing factor

   –

   Remediation

   • Rolled Supavisor back to the previous version

   Action items

   • Cut rollback time from 40 minutes to under 90 seconds
   • Detect client disconnections within 2 minutes

   Lessons

   Rollback was too slow and the pooler was not resilient enough to unforeseen failures under load; future work focuses on faster rollbacks to reduce the impact of similar failed deployments.

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